Use the open source, cloud APIs, or public libraries listed in your application development based on your technology preferences, such as primary language. The list also provides a view of the components' rating on different dimensions such as community support availability, security vulnerability, and overall quality, helping you make an informed choice for implementation and maintenance of your application. Please review the components carefully, having a no license alert or proprietary license, and use them appropriately in your applications. Please check the component page for the exact license of the component. You can also get information on the component's features, installation steps, top code snippets, and top community discussions on the component details page. The links to package managers are listed for download, where packages are readily available. Otherwise, build from the respective repositories for use in your application. You can also use the source code from the repositories in your applications based on the respective license types.

Student's performance prediction is essential to be conducted for a university/educational institutes to prevent student fail. Extensive efforts have been made in order to predict student performance for different aims, like: detecting at risk students, assurance of student retention, course and resource allocations, and many others. In this challenge, we are inviting to build a solution for student performance prediction which would help to detect at risk students and drop out. You can extend the factors for this prediction as per your choice. Please see below a sample solution kit to jumpstart your solution on student performance prediction. To use this kit to build your own solution, scroll down to refer sections Kit Deployment Instructions and Instruction to Run

The fact that Python allows writing effective code in fewer LOCs compared to other programming languages makes it a great tool for blockchain coding. The white spaces in Python programming can be used as code blocks, eliminating the need for curly brackets - just one of the many simplicities of this coding language. With Python, a developer can create a simple blockchain in fewer than 50 lines of code! Furthermore, Python supports a stable framework to handle the huge influx of queries characteristic of blockchains. The command-line tools available in Python enable developers to code blockchain certificates.

Scroll over to this list of the 24 best open-source blockchain libraries coded in Python. The top ranker is the LBRY code package built on Python and asyncio. This library provides a data network of seeders and peers that are discoverable to each other. Another high-utility code package for blockchains from this list is the Electrum library, which provides pre-written code to develop a Bitcoin wallet app. If you need a database code, BigchainDB is the library to have - it provides a repository for the BigchainDB servers